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Researchers uncover way for current supercomputers to replicate human brain

New algorithm doesn't use any more computer memory, researchers claim

Researchers from around the world have joined forces in a bid to create the technology to achieve simulations that replicate the human brain.

Published in Frontiers in Neuroinformatics, the breakthrough indicates how larger parts of the human brain can be represented without needing to use any more computer memory.

As a result, the brain-scale networks of the exascale class could be seen on supercomputers of today, the researchers said. They attribute this to a new algorithm that significantly speeds up brain simulations on existing computers, because the memory required on each node no longer increases with network size.

For example, at the beginning of the brain-level simulation, the new technology allows the nodes to exchange information about who needs to send neuronal activity data to whom, the researchers explained.

Once this knowledge is available, the exchange of neuronal activity data between nodes can be organised such that a node only receives the information it requires. And so an additional 'bit' for each neuron in the network is no longer necessary.

"The human brain is an organ of incredible complexity, composed of 100 billion inter-connected nerve cells," the researchers said. "However, even with the help of the most powerful supercomputers available, it is currently impossible to simulate the exchange of neuronal signals in networks of this size."

Markus Diesmann, director at the Jülich Institute of Neuroscience and Medicine, added that in order to achieve this, the software requires the entire main memory of petascale supercomputers.

Working for more than 20 years on the simulation software NEST, Diesmann said the behaviour of each neuron in the network is represented by a handful of mathematical equations.

"Future exascale computers, such as the post-K computer planned in Kobe and JUWELS in Jülich, will exceed the performance of today's high-end supercomputers by 10- to 100-fold," the report said.

"For the first time, researchers will have the computer power available to simulate neuronal networks on the scale of the human brain."